{"title":"雾计算环境下基于边缘亲和力的应用管理","authors":"Md. Redowan Mahmud, K. Ramamohanarao, R. Buyya","doi":"10.1145/3344341.3368795","DOIUrl":null,"url":null,"abstract":"Fog computing overcomes the limitations of executing Internet of Things (IoT) applications in remote Cloud datacentres by extending the computation facilities closer to data sources. Since most of the Fog nodes are resource constrained, accommodation of every IoT application within Fog environments is very challenging. Hence, we need to efficiently identify which set of applications should be deployed in Fog. It becomes even more complicated when the application characteristics in terms of urgency, size and flow of inputs are considered simultaneously. The necessity of time-optimized execution further intensifies the application management problem. In this work, we propose a policy for Fog environments that distributes application management tasks across the gateway and the infrastructure level. It classifies and places applications according to their Edge affinity. Edge affinity of an application denotes the relative intensity of different attributes coherent with its characteristics such as user-defined deadline, amount of data per input and sensing frequency of IoT devices, which are required to be addressed within Fog environments to meet its Quality of Service (QoS). The proposed policy also minimizes the service delivery time of applications in Fog infrastructure. Its performance is compared with existing application management policies in both iFogSim-simulated and FogBus-based real environments. The experiment results show that our policy outperforms others in combined QoS enhancement, network relaxation and resource utilization.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"Edge Affinity-based Management of Applications in Fog Computing Environments\",\"authors\":\"Md. Redowan Mahmud, K. Ramamohanarao, R. Buyya\",\"doi\":\"10.1145/3344341.3368795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fog computing overcomes the limitations of executing Internet of Things (IoT) applications in remote Cloud datacentres by extending the computation facilities closer to data sources. Since most of the Fog nodes are resource constrained, accommodation of every IoT application within Fog environments is very challenging. Hence, we need to efficiently identify which set of applications should be deployed in Fog. It becomes even more complicated when the application characteristics in terms of urgency, size and flow of inputs are considered simultaneously. The necessity of time-optimized execution further intensifies the application management problem. In this work, we propose a policy for Fog environments that distributes application management tasks across the gateway and the infrastructure level. It classifies and places applications according to their Edge affinity. Edge affinity of an application denotes the relative intensity of different attributes coherent with its characteristics such as user-defined deadline, amount of data per input and sensing frequency of IoT devices, which are required to be addressed within Fog environments to meet its Quality of Service (QoS). The proposed policy also minimizes the service delivery time of applications in Fog infrastructure. Its performance is compared with existing application management policies in both iFogSim-simulated and FogBus-based real environments. The experiment results show that our policy outperforms others in combined QoS enhancement, network relaxation and resource utilization.\",\"PeriodicalId\":261870,\"journal\":{\"name\":\"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3344341.3368795\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3344341.3368795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge Affinity-based Management of Applications in Fog Computing Environments
Fog computing overcomes the limitations of executing Internet of Things (IoT) applications in remote Cloud datacentres by extending the computation facilities closer to data sources. Since most of the Fog nodes are resource constrained, accommodation of every IoT application within Fog environments is very challenging. Hence, we need to efficiently identify which set of applications should be deployed in Fog. It becomes even more complicated when the application characteristics in terms of urgency, size and flow of inputs are considered simultaneously. The necessity of time-optimized execution further intensifies the application management problem. In this work, we propose a policy for Fog environments that distributes application management tasks across the gateway and the infrastructure level. It classifies and places applications according to their Edge affinity. Edge affinity of an application denotes the relative intensity of different attributes coherent with its characteristics such as user-defined deadline, amount of data per input and sensing frequency of IoT devices, which are required to be addressed within Fog environments to meet its Quality of Service (QoS). The proposed policy also minimizes the service delivery time of applications in Fog infrastructure. Its performance is compared with existing application management policies in both iFogSim-simulated and FogBus-based real environments. The experiment results show that our policy outperforms others in combined QoS enhancement, network relaxation and resource utilization.